The Power of Artificial Intelligence on Drug Manufacturing and Clinical Trials
Keywords:
Artificial Intelligence, Machine Learning, Drug Discovery, Drug Development, Clinical Trials, Pharmaceutical Industry, Healthcare, Ethics
Abstract
Artificial intelligence (AI) and machine learning (ML) have become significant aspects of contemporary society. The prominence of AI in society is attributed to its vital role in different quotas of life, that is, by using "big data" to perform tasks that would be impossible or take long to be done by a human. These functions are achieved by perceiving, synthesizing, and inferring information performed by computerized machines instead of intelligence possessed by animals or humans. For example, in the pharmaceutical industry, AI technology is used to improve efficiency and accuracy in manufacturing drugs and their performance in improving health care. This study takes responsibility to look into aspects impacted by artificial intelligence in the modern pharmaceutical industry. Aspects studied herein include the impact of AI and the time taken to discover and develop drugs, the consumer cost of the drugs developed with AI/ML technology, its impact on medical education, and ethical issues associated with the related technology, notwithstanding the impacts of AI/ML on clinical trials. The study found that AI and ML significantly impact the time taken to discover drugs, and the technology in discussion contributed to consumer cost reduction. Furthermore, it has contributed to the need for revising the medical curriculum; even with the ethical concerns on the safety and privacy of data utilized in the technology, it has significantly led to significant changes in the clinical trials of drug discovery and development methodologies.
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Baron, J. (2012). Evolution of clinical research: A history before and beyond James Lind. Perspectives in Clinical Research, 3(4), 149. https://doi.org/10.4103/2229-3485.103599
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Johnson, K. B., Wei, W., Weeraratne, D., Frisse, M. E., Misulis, K., Rhee, K., Zhao, J., & Snowdon, J. L. (2020). Precision Medicine, AI, and the Future of Personalized Health Care. Clinical and Translational Science, 14(1). https://doi.org/10.1111/cts.12884
Kahn, J. (2021). Money is pouring into A.I.-assisted drug discovery, while fewer AI startups are getting VC backing. Fortune. https://fortune.com/2021/03/03/artificial-intelligence-ai-index-venture-capital-startup-funding/
Kelle, U. (2008). Combining qualitative and quantitative research methods to support psychosocial and mental health programmes in complex emergencies. Intervention, 6(3), 348. https://doi.org/10.1097/wtf.0b013e32831e12d4
Kiriiri, G. K., Njogu, P. M., & Mwangi, A. N. (2020). Exploring different approaches to improve the success of drug discovery and development projects: a review. Future Journal of Pharmaceutical Sciences, 6(1). https://doi.org/10.1186/s43094-020-00047-9
Kolluri, S., Lin, J., Liu, R., Zhang, Y., & Zhang, W. (2022). Machine Learning and Artificial Intelligence in Pharmaceutical Research and Development: a Review. The AAPS Journal, 24(1). https://doi.org/10.1208/s12248-021-00644-3
Kulkov, I. (2021). The role of artificial intelligence in business transformation: A case of pharmaceutical companies. Technology in Society, 66, 101629. https://doi.org/10.1016/j.techsoc.2021.101629
Liebman, M. (2022). The Role of Artificial Intelligence in Drug Discovery and Development. Chemistry International, 44(1), 16–19. https://doi.org/10.1515/ci-2022-0105
Liu, Z., Roberts, R. A., Lal-Nag, M., Chen, X., Huang, R., & Tong, W. (2021). AI-based language models powering drug discovery and development. Drug Discovery Today, 26(11), 2593–2607. https://doi.org/10.1016/j.drudis.2021.06.009
Londhe, V. Y., & Bhasin, B. (2019). Artificial intelligence and its potential in oncology. Drug Discovery Today, 24(1), 228–232. https://doi.org/10.1016/j.drudis.2018.10.005
Merck. (2022). Merck Announces the Launch of the Merck Digital Sciences Studio to Help Healthcare Startups Quickly Bring their Innovations to Market. Merck.com. https://www.merck.com/news/merck-announces-the-launch-of-the-merck-digital-sciences-studio-to-help-healthcare-startups-quickly-bring-their-innovations-to-market/
Novartis. (2021). The art of drug design in a technological age. Novartis. https://www.novartis.com/stories/art-drug-design-technological-age
NW, 1615 L. S., Suite 800Washington, & Inquiries, D. 20036USA202-419-4300 | M.-8.-8. | F.-4.-4. | M. (2020, June 30). 5. Tech causes more problems than it solves. Pew Research Center: Internet, Science & Tech. https://www.pewresearch.org/internet/2020/06/30/tech-causes-more-problems-than-it-solves/
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Patel, V., & Shah, M. (2021). A comprehensive study on artificial intelligence and machine learning in drug discovery and development. Intelligent Medicine, 2(3). https://doi.org/10.1016/j.imed.2021.10.001
Paul, D., Sanap, G., Shenoy, S., Kalyane, D., Kalia, K., & Tekade, R. K. (2020). Artificial intelligence in drug discovery and development. Drug Discovery Today, 26(1). NCBI. https://doi.org/10.1016/j.drudis.2020.10.010
Pfizer.com. (2021). Artificial Intelligence: On a mission to Make Clinical Drug Development Faster and Smarter | Pfizer. Pfizer.com. https://www.pfizer.com/news/articles/artificial_intelligence_on_a_mission_to_make_clinical_drug_development_faster_and_smarter
Pharmaceutical Technology. (2021, August 19). BMS to in-license Exscientia’s AI-driven drug candidate. Pharmaceutical Technology. https://www.pharmaceutical-technology.com/news/bms-exscientia-drug-candidate/
Radin, A. (2017). Artificial Intelligence in Drug Discovery: An Evolution, Not a Revolution. Drug Discovery from Technology Networks. https://www.technologynetworks.com/drug-discovery/articles/artificial-intelligence-in-drug-discovery-an-evolution-not-a-revolution-362386
roche.com. (2022). Roche | Harnessing the power of AI. Www.roche.com. https://www.roche.com/stories/harnessing-the-power-of-ai#:~:text=So%2C%20Genentech%20scientists%20are%20using
Sanofi. (2022). Exscientia and Sanofi establish strategic research collaboration to develop an AI-driven pipeline of precision-engineered medicines - Sanofi. Www.sanofi.com. https://www.sanofi.com/en/media-room/press-releases/2022/2022-01-07-06-00-00-2362917
Vamathevan, J., Clark, D., Czodrowski, P., Dunham, I., Ferran, E., Lee, G., Li, B., Madabhushi, A., Shah, P., Spitzer, M., & Zhao, S. (2019). Applications of machine learning in drug discovery and development. Nature Reviews Drug Discovery, 18(6), 463–477. https://doi.org/10.1038/s41573-019-0024-5
Wong, C. H., Siah, K. W., & Lo, A. W. (2018). Estimation of clinical trial success rates and related parameters. Biostatistics, 20(2), 273–286. https://doi.org/10.1093/biostatistics/kxx069
Wouters, O. J., McKee, M., & Luyten, J. (2020). Estimated Research and Development Investment Needed to Bring a New Medicine to Market, 2009-2018. JAMA, 323(9), 844. https://doi.org/10.1001/jama.2020.1166
Published
2023-06-09
How to Cite
Lainjo, B. (2023). The Power of Artificial Intelligence on Drug Manufacturing and Clinical Trials. European Journal of Science, Innovation and Technology, 3(3), 1-15. Retrieved from https://ejsit-journal.com/index.php/ejsit/article/view/193
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